Using randomised/high-entropy data is meant to improve the "fairness" of the benchmarks preventing "best-case" scenarios where results may be better than expected. While hardware may thus perform better given low-entropy data - that is preferable to the previous results.

- Ranker: old results (pre Sandra 2014) removed.

- The reference/aggregated results have been updated with newer 2017 results given higher weight.

further benchmarks will be enabled as tools are further updated to support more AVX512 intrinsics: - CPU Scientific: FFT (single and double floating-point) - CPU Image Processing: all applicable filters - other benchmarks may be updated CUDA has been temporarily removed due to tool change; based on testing either OpenCL or DirectX Compute GPGPU benchmarks perform similarly at this time. The .Net 4.7x CLR does not appear to use AVX512 yet - but as Sandra uses variable width vectors any future update will automagically use it.